考虑电动出租车随机概率行为特性的充电站规划

电动出租车的规模化运营需要以充电设施为支撑,考虑到时间价值对以盈利为目的的电动出租车驾驶员的重要性,以及出租车在选择充电站时兼顾时间损耗大小和寻找乘客便捷性的特点,基于效用函数建立了出租车对充电站的概率选择函数,进而构建全社会年总成本目标函数,以配电网容量和站址间距离为约束建立模型。基于排队理论的M/G/c模型,采用带约束条件的整数规划模型对充电站容量进行优化配置,通过改进的量子遗传算法实现电动出租车充电站的选址定容规划。最后,以49节点的路网和32节点的配电网为例说明了模型和方法的有效性和实用性。

Charging Station Planning Considering Probability Behavior Characteristic of Electric Taxi

The large scale operation of electric taxi needs the support of charging infrastructure. Take into account the time value to the taxi drivers and the consideration of convenience in finding passengers when they choose a charging station, a probability selection model based on utility function is given. Then the total social time cost in finding charging stations and passengers can be calculated. The minimum sum of total social time cost, investment of charging station and power losses is taken as the objective for the optimal planning of charging station location. The optimization configuration of charging stations is performed by utilizing the queuing theory M/G/c model. The whole planning model is solved by improved quantum genetic algorithm(IQGA). Finally, example analysis verifies the effectiveness and practicality of the planning method.